Assistant Manager, Statistics & Service Systems Development

About the role

The Land Transport Authority (LTA) is hiring an Assistant Manager for its Statistics and Service Systems Development team. You will join a team that designs and develops automation and AI solutions to transform how vehicle-related data services are delivered. The role sits within the LTA's division and involves working with rich datasets on vehicle-related statistics in Singapore.

Key responsibilities

• Build robotic process automation (RPA) workflows to streamline business processes.
• Develop and deploy AI-enabled tools, and create intuitive, well-designed dashboards and data products for internal and external stakeholders.
• Translate complex vehicle statistics into clear, visually compelling insights that support policy-making and appear in publications on the LTA and OneMotoring websites.
• Partner with the leadership team and internal and external stakeholders to identify automation opportunities, prototype solutions and drive adoption of digital tools across the division.

Required profile

• Knowledge in any discipline; a background in Computer Science, Information Technology, Data Science/Analytics or Design/Human-Computer Interaction is an advantage.
• Strong analytical skills, a meticulous approach and the ability to work with complex datasets.
• Good communication and interpersonal skills, able to present ideas clearly and collaborate with diverse stakeholders.
• A self-directed learner who keeps pace with emerging AI and automation technologies, and able to work independently in a fast-paced environment.

Required skills

• Hands-on experience developing RPA solutions (e.g. UiPath, Power Automate) and/or AI tools, including prompt engineering, machine learning applications or AI-assisted workflow design.
• Ability to design clean, user-friendly dashboards, visualisations and reports for non-technical audiences.
• Proficiency in data visualisation tools such as Power BI or Tableau.
• Familiarity with Python, SQL and relational databases (e.g. IBM Query Management Facility) is an advantage.